Kumar K.

Most AI applications look impressive in a demo. The difficult part is making them useful when they meet real data, real users and real business workflows — where unreliable retrieval, hallucinations, failed API calls and broken workflows can quickly become business problems. That's how I approach AI engineering: start with the problem, design the right system, and build it to work beyond the demo. I’m a Top Rated Plus AI Engineer with $600K+ earned on Upwork, 100% Job Success, and 12+ years of software engineering and product-development experience. I'm also a Kaggle Expert ranked in the Top 4% globally (#2,226 of 59,691), with a Bronze Notebook Medal, giving me hands-on experience solving real ML problems competitively. Cardio Scholar is an AI research automation system built for a cardiology client. It connects to PubMed, processes new research with Gemini, and delivers structured results through an automated n8n workflow, REST API and admin panel — helping the team spend less time manually searching and summarizing research. Multi-Source Research Agent autonomously plans research, searches and scrapes up to 8 sources, synthesizes the findings and produces a finished report. It includes model failover between Gemini and Llama to keep the workflow running when a model becomes unavailable. Multi-Source RAG Assistant uses four different paths — direct LLM, private knowledge base, web research and multi-source research — so questions can be answered using the information source that actually fits the task. Mindfulness Greece, a consumer mobile product I built, has reached 400K+ downloads and ranked above Calm and Headspace in the Greek App Store. I've spent years taking software from development to deployment and real-world use — experience I now bring to AI systems. I also have hands-on ML/DL experience, including a bankruptcy prediction system across 6,819 companies and 94 financial features that achieved 0.9367 ROC-AUC with XGBoost. The stack I work with includes Python, FastAPI, LangGraph, LangChain, LlamaIndex, OpenAI, Claude, Gemini, HuggingFace, ChromaDB, Pinecone, FAISS, n8n, PyTorch, XGBoost, Docker, GitHub and AWS. If you're building an AI agent, RAG system, LLM application, AI automation, Voice AI product or AI-powered SaaS and want an engineer who can think beyond the model and build the surrounding system properly, let's talk.